1. Field of the Invention
The present invention relates to a binary (black and white) image pattern identification/recognition method.
2. Related Technologies
In a conventional character recognition processor and an image recognition processor including a kanji (Chinese-character-reading) OCR (Optical Character Reader), some distinctive features of Chinese characters and other symbols are selected from characters and image patterns in the form of vectors to be compared to reference pattern vectors in each of the categories in a standard dictionary created in advance so as to be able to perform discriminant functions such as those detecting similarity or distance, thus identifying the most similar character or image pattern as a result.
Conventional character recognition systems widely use the so-called "structural feature" which corresponds to character line structures such as line direction, connection relationship, and positional definition. However, in the case of specially designed characters having an unusual texture, unclear characters, or images which cause significant background noise, the "structural feature" is significantly distorted, which significantly degrades the accuracy of recognition.
Moreover, simple degree of similarity (hereafter, referred to as "similarity degree") is also known as a discriminant function based on the number of black pixels common to a binary image entered and the reference pattern vectors (also represented in a binary pattern) of each category in the standard dictionary prepared in advance. However, this method has a problem in that specially designed characters having an unusual texture or images having significant background noise may be incorrectly identified as a category having more (or a larger number of) black pixels among the reference pattern vectors.
That is, the conventional OCR technology or other recognition technologies are not free from the problem that specially designed characters, unclear characters, characters having significant background noise or reverse contrast characters (white characters against a black background) cannot be recognized correctly.